While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!We are seeking a skilled and passionate ML Engineer with 7+ years of experience to join our team. The ideal candidate will be instrumental in developing, deploying, and maintaining machine learning models, with a strong focus on MLOps practices. This role requires hands-on experience with Azure cloud services, Databricks, and MLflow to build robust and scalable ML solutions.
Responsibilities
- Design, develop, and implement machine learning models and algorithms to solve complex business problems.
- Collaborate with data scientists to transition models from research and development to production-ready systems.
- Build and maintain scalable data pipelines for ML model training and inference using Databricks.
- Implement and manage the ML model lifecycle using MLflow for experiment tracking, model versioning, and model registry.
- Deploy and manage ML models in production environments on Azure, leveraging services like Azure Machine Learning, Azure Kubernetes Service (AKS), or Azure Functions.
- Support MLOps workloads by automating model training, evaluation, deployment, and monitoring processes.
- Ensure the reliability, performance, and scalability of ML systems in production.
- Monitor model performance, detect drift, and implement retraining strategies.
- Collaborate with DevOps and Data Engineering teams to integrate ML solutions into existing infrastructure and CI/CD pipelines.
- Document model architecture, data flows, and operational procedures. Qualifications.
Skills
- Strong proficiency in Python programming for data manipulation, machine learning, and scripting.
- Hands-on experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or Keras.
- Demonstrated experience with MLflow for experiment tracking, model management, and model deployment.
- Proven experience working with Microsoft Azure cloud services, specifically Azure Machine Learning, Azure Databricks, and related compute/storage services.
- Solid experience with Databricks for data processing, ETL, and ML model development.
- Understanding of MLOps principles and practices, including CI/CD for ML, model versioning, monitoring, and retraining.
- Experience with containerization technologies (Docker) and orchestration (Kubernetes, especially AKS) for deploying ML models.
- Familiarity with data warehousing concepts and SQL.
- Ability to work with large datasets and distributed computing frameworks.
- Strong problem-solving skills and attention to detail.
- Excellent communication and collaboration skills.
Nice-to-Have Skills
- Experience with other cloud platforms (AWS, GCP).
- Knowledge of big data technologies like Apache Spark.
- Experience with Azure DevOps for CI/CD pipelines.
- Familiarity with real-time inference patterns and streaming data.
- Understanding of responsible AI principles (fairness, explainability, privacy).
Certifications
- Microsoft Certified: Azure AI Engineer Associate
- Databricks Certified Machine Learning Associate (or higher)
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
